基于快速粒子群算法的蒸发过程优化控制

doi:10.12034/j.issn.1009-606X.216286

过程工程学报 ›› 2017, Vol. 17 ›› Issue (3): 539-544.DOI: 10.12034/j.issn.1009-606X.216286

基于快速粒子群算法的蒸发过程优化控制

柴琴琴^1,2*，林琼斌¹，林双杰¹

1. 福州大学电气工程与自动化学院，福建福州 350108；2. 福州大学先进控制技术研究中心，福建福州 350108

收稿日期:2016-08-30 修回日期:2016-12-12 出版日期:2017-06-20 发布日期:2017-06-14
通讯作者: 柴琴琴 kppqing@163.com
基金资助:
福建省自然科学基金项目

Optimal Control of an Evaporation Process Using a Fast Particle Swarm Optimization Algorithm

Qinqin CHAI^1,2*, Qiongbin LIN¹, Shuangjie LIN¹

1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, Fujian 350108, China;
2. Research Center for Advanced Process Control, Fuzhou University, Fuzhou, Fujian 350108, China

Received:2016-08-30 Revised:2016-12-12 Online:2017-06-20 Published:2017-06-14
Contact: Qin-Qin CHAI kppqing@163.com

摘要/Abstract

摘要：

基于欧拉法，改进了蒸发过程离散时滞动态模型，构建了在线非线性预测控制模型. 针对时滞系统小采样周期与长预测控制域带来的计算负担，提出了快速粒子群算法的求解方法，保证控制实时性. 实例模拟表明，在采样时间足够小时仍能保证实时性，液位和浓度很快达到设定范围，新蒸汽消耗量下降1%，可节约蒸汽0.6 t/h.

关键词: 蒸发过程, 优化控制, 时滞, 粒子群算法

Abstract:

Using the improved Euler method, a discrete dynamic model for evaporation process was firstly built. Then a nonlinear prediction control model was constructed. For time-delayed system, the sampling period should be small but the prediction control period should be long. These time requirements resulted in serious computational burden. To improve computational speed, a fast particle swarm algorithm was proposed to ensure the real-time control. And simulation results of a real evaporation process showed that even the sampling time was enough small. In addition, the levels and concentration reach the desired range in a short time, and the live steam consumption was decreased by 1% and saved about 0.6 t/h.

Key words: evaporation process, optimal control, time delay, particle swarm optimization

柴琴琴林琼斌林双杰. 基于快速粒子群算法的蒸发过程优化控制[J]. 过程工程学报, 2017, 17(3): 539-544.

Qinqin CHAI Qiongbin LIN Shuangjie LIN. Optimal Control of an Evaporation Process Using a Fast Particle Swarm Optimization Algorithm[J]. Chin. J. Process Eng., 2017, 17(3): 539-544.

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基于快速粒子群算法的蒸发过程优化控制

Optimal Control of an Evaporation Process Using a Fast Particle Swarm Optimization Algorithm

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